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DeepSeek R1 Distill 7B vs Mistral 7B
Which runs better on your device? Side-by-side comparison of specs, quantization sizes, and device compatibility.
SPECIFICATIONS
Type
Reasoning
Reasoning
Parameters
7.62B
7.24B
Context
128K
32K
Min tier
High
High
Runs on
47 / 47 devices
47 / 47 devices
QUANTIZATION SIZES
| Quant | DeepSeek R1 Distill 7B | Mistral 7B | |
|---|---|---|---|
| FP16 | 15.5 GB | 14.7 GB | Mistral 7B smaller |
| Q8 | 8.1 GB | 8.2 GB | DeepSeek R1 Distill 7B smaller |
| Q6 | 5.9 GB | 5.9 GB | |
| Q5 | 5.1 GB | 4.9 GB | Mistral 7B smaller |
| Q4 | 4.4 GB | 4.1 GB | Mistral 7B smaller |
| Q3 | 3.3 GB | 3.1 GB | Mistral 7B smaller |
| Q2 | 2.5 GB | 2.3 GB | Mistral 7B smaller |
DEVICE COMPATIBILITY
| Device | DeepSeek R1 Distill 7B | Mistral 7B |
|---|---|---|
| 💻 MacBook Air M4 macOS | Runs well Q8 · ~15 tok/s | Runs well Q8 · ~15 tok/s |
| 💻 MacBook Air M3 macOS | Runs well Q8 · ~12 tok/s | Runs well Q8 · ~12 tok/s |
| 💻 MacBook Air M2 macOS | Tight fit Q5 · ~20 tok/s | Tight fit Q5 · ~20 tok/s |
| 💻 MacBook Pro M4 Pro macOS | Runs great FP16 · ~18 tok/s | Runs great FP16 · ~19 tok/s |
| 💻 MacBook Air M1 macOS | Tight fit Q5 · ~13 tok/s | Tight fit Q5 · ~14 tok/s |
| 💻 MacBook Air M1 macOS | Runs well Q8 · ~8 tok/s | Runs well Q8 · ~8 tok/s |
| 💻 MacBook Pro M1 macOS | Runs well Q8 · ~8 tok/s | Runs well Q8 · ~8 tok/s |
| 💻 MacBook Pro M1 Pro macOS | Runs well Q8 · ~25 tok/s | Runs well Q8 · ~24 tok/s |
| 💻 MacBook Pro M1 Pro macOS | Runs well FP16 · ~13 tok/s | Runs well FP16 · ~14 tok/s |
| 💻 MacBook Pro M1 Max macOS | Runs well FP16 · ~26 tok/s | Runs well FP16 · ~27 tok/s |
| 💻 MacBook Pro M1 Max macOS | Runs great FP16 · ~26 tok/s | Runs great FP16 · ~27 tok/s |
| 💻 MacBook Pro M2 Pro macOS | Runs well Q8 · ~25 tok/s | Runs well Q8 · ~24 tok/s |
| 💻 MacBook Pro M2 Pro macOS | Runs well FP16 · ~13 tok/s | Runs well FP16 · ~14 tok/s |
| 💻 MacBook Pro M2 Max macOS | Runs well FP16 · ~26 tok/s | Runs well FP16 · ~27 tok/s |
| 💻 MacBook Pro M2 Max macOS | Runs great FP16 · ~26 tok/s | Runs great FP16 · ~27 tok/s |
| 💻 MacBook Pro M3 Pro macOS | Runs well Q8 · ~19 tok/s | Runs well Q8 · ~18 tok/s |
| 💻 MacBook Pro M3 Pro macOS | Runs great FP16 · ~10 tok/s | Runs great FP16 · ~10 tok/s |
| 💻 MacBook Pro M3 Max macOS | Runs great FP16 · ~26 tok/s | Runs great FP16 · ~27 tok/s |
| 💻 MacBook Pro M3 Max macOS | Runs great FP16 · ~26 tok/s | Runs great FP16 · ~27 tok/s |
| 📱 iPhone 16 Pro iOS | Tight fit Q3 · ~14 tok/s | Tight fit Q3 · ~15 tok/s |
| 📱 iPhone 15 iOS | Tight fit Q2 · ~12 tok/s | Tight fit Q2 · ~13 tok/s |
| 📱 Galaxy S25 Ultra Android | Tight fit Q4 · ~12 tok/s | Tight fit Q5 · ~11 tok/s |
| 📱 Galaxy S24 Android | Tight fit Q3 · ~13 tok/s | Tight fit Q3 · ~14 tok/s |
| 📱 Pixel 9 Pro Android | Tight fit Q6 · ~8 tok/s | Tight fit Q6 · ~8 tok/s |
| 🎮 Steam Deck OLED Linux | Runs well Q8 · ~11 tok/s | Runs well Q8 · ~11 tok/s |
| 🖥️ Gaming PC (RTX 4070) Windows | Runs well Q8 · ~62 tok/s | Runs well Q8 · ~61 tok/s |
| 🖥️ Gaming PC (RTX 3060) Windows | Runs well Q8 · ~44 tok/s | Runs well Q8 · ~44 tok/s |
| 🖥️ Gaming PC (RTX 4080) Windows | Runs great Q8 · ~89 tok/s | Runs great Q8 · ~87 tok/s |
| 🖥️ Gaming PC (RTX 4090) Windows | Runs well FP16 · ~65 tok/s | Runs well FP16 · ~69 tok/s |
| 🤖 Atom 1 Linux | Runs well FP16 · ~13 tok/s | Runs well FP16 · ~14 tok/s |
| 🤖 Atom 1 Linux | Runs great FP16 · ~18 tok/s | Runs great FP16 · ~19 tok/s |
| 🤖 Atom 1 Linux | Runs great FP16 · ~18 tok/s | Runs great FP16 · ~19 tok/s |
| 📱 iPad Pro M4 iOS | Tight fit Q6 · ~14 tok/s | Tight fit Q6 · ~14 tok/s |
| 🖥️ Mac Mini M1 macOS | Tight fit Q5 · ~13 tok/s | Tight fit Q5 · ~14 tok/s |
| 🖥️ Mac Mini M1 macOS | Runs well Q8 · ~8 tok/s | Runs well Q8 · ~8 tok/s |
| 🖥️ Mac Mini M2 macOS | Tight fit Q5 · ~20 tok/s | Tight fit Q5 · ~20 tok/s |
| 🖥️ Mac Mini M2 Pro macOS | Runs well Q8 · ~25 tok/s | Runs well Q8 · ~24 tok/s |
| 🖥️ Mac Mini M2 Pro macOS | Runs well FP16 · ~13 tok/s | Runs well FP16 · ~14 tok/s |
| 🖥️ Mac Mini M4 macOS | Runs well Q8 · ~15 tok/s | Runs well Q8 · ~15 tok/s |
| 🖥️ Mac Mini M4 macOS | Runs well FP16 · ~8 tok/s | Runs well FP16 · ~8 tok/s |
| 🖥️ Mac Mini M4 Pro macOS | Tight fit FP16 · ~18 tok/s | Tight fit FP16 · ~19 tok/s |
| 🖥️ Mac Mini M4 Pro macOS | Runs great FP16 · ~18 tok/s | Runs great FP16 · ~19 tok/s |
| 🖥️ Mac Studio M4 Max macOS | Runs great FP16 · ~35 tok/s | Runs great FP16 · ~37 tok/s |
| 🖥️ Mac Pro M2 Ultra macOS | Runs great FP16 · ~52 tok/s | Runs great FP16 · ~54 tok/s |
| 💻 Snapdragon X Elite Laptop Windows | Runs well Q8 · ~17 tok/s | Runs well Q8 · ~17 tok/s |
| 📱 OnePlus 13 Android | Tight fit Q6 · ~9 tok/s | Tight fit Q6 · ~9 tok/s |
| 🍓 Raspberry Pi 5 Linux | Tight fit Q6 · ~5 tok/s | Tight fit Q6 · ~5 tok/s |
VERDICT
Both models run on 47 of 47 devices. DeepSeek R1 Distill 7B has a larger context window (128K vs 32K). DeepSeek R1 Distill 7B is the larger model and may produce better quality outputs, while Mistral 7B is lighter on resources. For memory-constrained devices, Mistral 7B is smaller at its lowest quant (2.3 GB vs 2.5 GB).